ABSTRACT
The advances in Assisted Reproductive Technologies (ARTs) applied in South American camelid species are still scarce. The aim of this study was to compare the effects of three semen extenders, before and after the cryopreservation of spermatozoa obtained from the vas deferens, on sperm quality parameters and in vitro fertilization rates of llama (Lama glama) oocytes. Mature fertile llama males (Lama glama; n = 6; age: 48-60 mo.; BCS: ~2.7) were included in the study. Sperm samples were collected from each male using the surgical technique of the vas deferens deviation. Then, the sperm samples were pooled and diluted with the Tris-EY, Andromed®, or BioxCell® extender in order to subsequently carry out the sperm cryopreservation process. The sperm quality assessment related to each extender was performed before and after cryopreservation with regard to sperm morphological abnormalities, acrosome integrity, sperm viability, membrane permeability, and sperm motility traits. Moreover, in vitro fertilization (IVF) procedures were carried out to evaluate the in vitro fertility of the cryopreserved sperm samples using each extender. Overall, significant differences were observed before and after cryopreservation regarding acrosome integrity, sperm viability, membrane permeability, and sperm motility traits among the extenders used, where Tris-EY and Andromed® were better than BioxCell® (p < 0.05); however, no differences were observed regarding the sperm morphological abnormalities among extenders (p > 0.05). Moreover, multiple differences were observed with regard to the velocity and linearity kinematic parameters obtained by computerized analysis before and after the cryopreservation process, irrespective of the extender used (p < 0.05). Finally, differences were observed regarding the in vitro fertilization rates among the different extender-derived samples (p < 0.05). In conclusion, the sperm quality using Tris-EY and Andromed® was better before and after cryopreservation compared to that using BioxCell®. Although the number of fertilized oocytes obtained after the IVF process between Tris-EY and Andromed® was similar, Andromed®-derived samples showed the best sperm quality results before and after cryopreservation. This indicates that the cryopreservation extender is a determining factor in significantly improving in vitro fertilization rates when using sperm samples obtained from vas deferens in llama (Lama glama) males.
ABSTRACT
Milk production in the Andean highlands is variable over space and time. This variability is related to fluctuating environmental factors such as rainfall season which directly influence the availability of livestock feeding resources. The main aim of this study was to develop a time-series model to forecast milk production in a mountainous geographical area by analysing the dynamics of milk records thorough the year. The study was carried out in the Andean highlands, using time-series models of monthly milk records collected routinely from dairy cows maintained in a controlled experimental farm over a 9-year period (2008-2016). Several statistical forecasting models were compared. The Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percent Error (MAPE) were used as selection criteria to compare models. A relation between monthly milk records and the season of the year was modelled using seasonal autoregressive integrated moving average (SARIMA) methods to explore temporal redundancy (trends and periodicity). According to white noise residual test (Q = 13.951 and p = 0.052), Akaike Information Criterion and MAE, MAPE, and RMSE values, the SARIMA (1, 0, 0) x (2, 0, 0)12 time-series model resulted slightly better forecasting model compared to others. In conclusion, time-series models were promising, simple and useful tools for producing reasonably reliable forecasts of milk production thorough the year in the Andean highlands. The forecasting potential of the different models were similar and they could be used indistinctly to forecast the milk production seasonal fluctuations. However, the SARIMA model performed the best good predictive capacity minimizing the prediction interval error. Thus, a useful effective strategy has been developed by using time-series models to monitor milk production and alleviate production drops due to seasonal factors in the Andean highlands.